Sys.setenv(LANG = "en") #English
knitr::opts_chunk$set(echo = TRUE)
rm(list = ls())

path <- getwd()
setwd(path)

# packages
pacman::p_load(tidyverse, patchwork, plotly)


# Font for windows and mac
if (stringr::str_detect(path, pattern="D:")){ 
  
  theme_set(theme_classic(base_size = 10, base_family = "Arial"))        # For Windows

 } else{
  
  theme_set(theme_classic(base_size = 10, base_family = "HiraginoSans-W3"))  # For Mac OS
 }

options(scipen=10)

# annotation size
annotate_size <- 3

1 Data and anntation setting

# 2021Feb02
graphs_data <- readr::read_csv("output/time_series_data.csv")
## Parsed with column specification:
## cols(
##   .default = col_double(),
##   prefecture = col_character(),
##   date = col_date(format = ""),
##   kyujin_bairitsu = col_logical(),
##   prefec_zenkaku = col_character(),
##   year_month = col_character()
## )
## See spec(...) for full column specifications.
# graphs_data <- graphs_data %>% 
#   dplyr::rename(hogo_persons_total = persons_total,
#                 hogo_households_total = households_total)

graphs_data <- graphs_data %>% dplyr::filter(date >= "2019-01-01" & date <= "2020-09-01")

2 Employment rate and LFP/就業率と労働参加率

emp_labor <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = employment_rate, group= 1),
           stat = "identity", position = "identity", color = "gray30") + 
  geom_line(aes(x = year_month,y = labor_participation_rate, group = 1), 
             stat = "identity",position = "identity", color = "blue") +
  scale_y_continuous(breaks = seq(58,63,by = 1), limits = c(58,63)) +
  geom_vline(xintercept = "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(a) Employment and labor force") + 
    annotate(geom="text", x = "2019-05", y  = 61.2,
             label = "Employment rate", size = annotate_size, color = "gray30") +
 annotate(geom = "text", x = "2019-07", y  = 62.8,
             label = "Labor force participation rate", size = annotate_size, color = "blue" ) 

emp_labor <- emp_labor + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

emp_labor

ggplotly(emp_labor)
## Warning: `group_by_()` is deprecated as of dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.

3 Unemployment rate and jobs-to-applicants ratio/失業率と有効求人倍率

# graph
unemp_jobapps <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = unemployment_rate,  group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month,y = jobs_to_applicants_ratio,  group = 1), 
             stat = "identity",position = "identity", color = "gray30") +
  labs(title = "(b) Unemployment and jobs-to-applicants ratio", size = 0.4) +
  geom_vline(xintercept =  "2020-01",colour = "gray") +
  scale_y_continuous(expand = c(0,0),breaks = seq(0,3.5,by = 0.5), limits = c(0, 3.5)) +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank())+
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 0)) +
  theme(plot.title = element_text(size = 10)) +
  annotate(geom = "text", x = "2019-05", y = 2.7, label = "Unemployment rate", 
           size = annotate_size,color = "blue") +
  #annotate("segment", x = "2020-06", y = 3.0,
  #           xend =  "2020-06", yend  = 3.2,
  #           arrow = arrow(length = unit(0, "cm"), type = "closed")) +
  annotate(geom = "text", x= "2019-05", y =1.8,
             label=" Jobs-to-applicants ratio", size = annotate_size , color = "gray30") 
  #annotate("segment", x =  "2020-06", y = 1.0,
  #           xend =  "2020-06", yend  = 0.8,
  #           arrow = arrow(length = unit(0, "cm"), type = "closed"))

unemp_jobapps <- unemp_jobapps + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

unemp_jobapps

ggplotly(unemp_jobapps)

4 Suicide/自殺者数

suicide <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = suicide_total, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y = suicide_female, group = 1), 
             stat = "identity", position = "identity", color = "gray30") +
   geom_line(aes(x = year_month, y = suicide_male, group = 1), 
             stat = "identity",position = "identity", color = "brown") +
  scale_y_continuous(breaks = seq(0,2000,by = 500), limits = c(0,2000)) +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 0)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(c) The number of suicides") +
  annotate(geom = "text", x = "2019-02", y = 1800,
             label = "Total", size = annotate_size, color = "blue") +
  annotate(geom = "text", x = "2019-02", y  = 630,
             label = "Women", size = annotate_size, color = "gray30" ) +
annotate(geom = "text", x = "2019-02", y = 1300,
             label = "Men", size = annotate_size, color = "brown" ) 
  
suicide <- suicide + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

suicide

ggplotly(suicide)

5 Suicide(YOY)/自殺者数(対前年同期差)

yoy_suicide <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = yoy_suicide_total, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y =  yoy_suicide_female, group = 1), 
             stat = "identity", position = "identity", color = "gray30") +
   geom_line(aes(x = year_month, y =  yoy_suicide_male, group = 1), 
             stat = "identity",position = "identity", color = "brown") +
  scale_y_continuous(breaks = seq(-400, 400,by = 100), limits = c(-400,400)) + #2021Aug13  ylim -300 → -350
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(d) The number of suicides (year-on-year)") +
  annotate(geom = "text", x = "2020-07", y = 370,
             label = "Total", size = annotate_size , color = "blue") +
  annotate(geom = "text", x = "2020-03", y = 50,
             label = "Women", size = annotate_size, color = "gray30" ) +
  annotate(geom = "text", x = "2020-08", y = -40,
             label = "Men", size = annotate_size, color = "brown")  

yoy_suicide <- yoy_suicide + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

yoy_suicide

ggplotly(yoy_suicide)

6 Public assistance/生活保護

6.1 Recipients and recipients households/受給者数と受給世帯数

public_assistance <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = persons_receive_zenkoku, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y =  households_receive_zenkoku, group = 1),
            stat = "identity", position = "identity", color = "gray30") +
  scale_y_continuous(breaks = seq(1500000, 2100000, by = 100000), limits = c(1500000, 2100000)) +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(g) Public Assistance recipients and recipient households") +
  annotate(geom = "text", x = "2019-02", y = 2000000, hjust = 0,
             label = "Public Assistance recipients", size = annotate_size , color = "blue") +
  annotate(geom = "text", x = "2019-02", y = 1700000,  hjust = 0,
            label = "Public Assistance recipient households", size = annotate_size, color = "gray30" )
  #annotate(geom = "text", x = "2020-08", y = -70,
  #           label = "Men", size = annotate_size, color = "brown")  

public_assistance <- public_assistance + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

public_assistance

ggplotly(public_assistance)

6.2 Recipients and recipients households(YOY)/受給者数と受給世帯数(YOY)

public_assistance_yoy <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = yoy_persons_receive_zenkoku, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y =  yoy_households_receive_zenkoku, group = 1),
            stat = "identity", position = "identity", color = "gray30")+
  scale_y_continuous(breaks = seq(-30000, 3000, by = 10000), limits = c(-30000, 3000)) +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
  labs(title = "(g) Public Assistance recipients and recipient households (year-on-year)") +
  annotate(geom = "text", x = "2019-08", y = -17000, hjust = 0,
             label = "Public Assistance recipients", size = annotate_size , color = "blue") +
  annotate(geom = "text", x = "2019-08", y = 2000,  hjust = 0,
            label = "Public Assistance recipient households", size = annotate_size, color = "gray30" )

public_assistance_yoy <- public_assistance_yoy + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

public_assistance_yoy

ggplotly(public_assistance_yoy)

6.3 Recipient households by hosehold type/世帯類型別の受給世帯数

YOY_public_assistance <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = yoy_households_receive_elderly_zenkoku, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y =  yoy_households_receive_singlemother_zenkoku, group = 1),
            stat = "identity", position = "identity", color = "gray30",linetype="dashed") +
  geom_line(aes(x = year_month, y =  yoy_households_receive_disabled_zenkoku, group = 1),
            stat = "identity", position = "identity", color = "brown") +
  geom_line(aes(x = year_month, y =  yoy_households_receive_sick_zenkoku, group = 1),
            stat = "identity", position = "identity", color = "red") +
  geom_line(aes(x = year_month, y =  yoy_households_receive_others_zenkoku, group = 1)) +
   labs(title = "(h) Public Assistance recipient households by type (year-on-year)") +
   scale_y_continuous(limits = c(-12000,20000)) +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
  annotate(geom = "text", x = "2019-04", y = 14000, hjust = 0,
            label = "The elderly", size = annotate_size , color = "blue") +
  annotate(geom = "text", x = "2019-04", y = 6000, hjust = 0,
            label = "The disabled", size = annotate_size , color = "brown") +
  annotate(geom = "text", x = "2019-05", y = -3000, hjust = 0,
            label = "Single mothers", size = annotate_size , color = "gray30") +
  annotate(geom = "text", x = "2020-02", y = 0, hjust = 0,
            label = "Others", size = annotate_size , color = "black") +
  annotate(geom = "text", x = "2020-04", y = -10000, hjust = 0,
            label = "The sick", size = annotate_size , color = "red") 

YOY_public_assistance <- YOY_public_assistance + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

YOY_public_assistance

ggplotly(YOY_public_assistance)

7 2nd-tier programs/緊急小口と総合支援と住居確保給付金

7.1 Emergency SA Funds and General Support Funds/緊急小口と総合支援

# 2020Jan29
poverty_programs <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y =  koguchi_number, group = 1), 
             stat = "identity", position = "identity", color = "blue") +
  geom_line(aes(x = year_month, y =  sogo_number, group = 1), 
             stat = "identity", position = "identity", color = "gray30") +
  #scale_y_continuous(breaks = seq(-300, 350,by = 100), limits = c(-300,350)) +
  scale_y_continuous(limits = c(0,200000)) +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(f) Accepted applications for emergency loans") +
  annotate(geom = "text", x = "2020-02", y = 150000, hjust = 1,
             label = "Emergency Small Ammount Funds", size = annotate_size, color = "blue" ) +
  annotate(geom = "text", x = "2020-02", y = 75000, hjust = 1,
             label = "General Support Funds", size = annotate_size, color = "gray30" ) 
 
poverty_programs <- poverty_programs + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

poverty_programs

ggplotly(poverty_programs)

7.2 Housing Security Benefit/住居確保給付金

# 2020Jan29
jukyo_number <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = jukyo_number, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  #scale_y_continuous(breaks = seq(-300, 350,by = 100), limits = c(-300,350)) +
  geom_vline(xintercept =  "2020-01", colour = "gray30") +
    scale_y_continuous(limits = c(0,40000)) +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(g) Accepted applications for Housing Security Benefit") +
  annotate(geom = "text", x = "2019-09", y = 20000,
             label = "Housing Security Benefit", size = annotate_size , color = "blue")
 
jukyo_number <- jukyo_number + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

jukyo_number

ggplotly(jukyo_number)

7.3 2nd-tier progrms/緊急小口・総合支援・住居確保

# 2020Jan29
safety_net <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y =  koguchi_number, group = 1), 
             stat = "identity", position = "identity", color = "blue") +
  geom_line(aes(x = year_month, y =  sogo_number, group = 1), 
             stat = "identity", position = "identity", color = "gray30") +
  geom_line(aes(x = year_month, y = jukyo_number, group = 1),
           stat = "identity", position = "identity", color = "brown") + 
  geom_vline(xintercept =  "2020-01", colour = "gray30") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
  theme(plot.title = element_text(size = 10)) +
   scale_y_continuous(limits = c(0,200000)) +
  labs(title = " (f) Accepted applications for second-tier safety net programs") +
  annotate(geom = "text", x = "2020-03", y = 150000, hjust = 1,
             label = "Emergency Small Ammount Funds", size = annotate_size, color = "blue" ) +  
  annotate(geom = "text", x = "2020-03", y = 75000, hjust = 1,
             label = "General Support Funds", size = annotate_size, color = "gray30" )  +
  annotate(geom = "text", x = "2020-03", y = 20000, hjust = 1,
             label = "Housing Security Benefit", size = annotate_size , color = "brown") 
 
safety_net <- safety_net + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

safety_net

ggplotly(safety_net)

8 Unemployment benefit/失業給付

失業等給付の基本手当

8.1 Recipients/失業給付受給者実人数

unemp_benefit_number <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = unemp_benefit_number_total, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y = unemp_benefit_number_female, group = 1), 
             stat = "identity", position = "identity", color = "gray30") +
   geom_line(aes(x = year_month, y = unemp_benefit_number_male, group = 1), 
             stat = "identity",position = "identity", color = "brown") +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  scale_y_continuous(limits = c(0,600000)) +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 0)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(e) Unemployment Benefit recipients") +
  annotate(geom = "text", x = "2019-02", y = 400000,
             label = "Total", size = annotate_size, color = "blue") +
  annotate(geom = "text", x = "2019-02", y  = 250000,
             label = "Women", size = annotate_size, color = "gray30" ) +
  annotate(geom = "text", x = "2019-02", y = 100000,
             label = "Men", size = annotate_size, color = "brown" ) 

unemp_benefit_number <- unemp_benefit_number + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

unemp_benefit_number 

ggplotly(unemp_benefit_number)

8.2 Recipients(YOY)/失業給付受給者実人数(YOY)

yoy_unemp_benefit_number <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = yoy_unemp_benefit_number_total, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y = yoy_unemp_benefit_number_female, group = 1), 
             stat = "identity", position = "identity", color = "gray30") +
   geom_line(aes(x = year_month, y = yoy_unemp_benefit_number_male, group = 1), 
             stat = "identity",position = "identity", color = "brown") +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  #scale_y_continuous(limits = c(0,600000)) +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 0)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "(e) Unemployment Benefit recipients (year-on-year)") +
  annotate(geom = "text", x = "2020-05", y = 100000,
              label = "Total", size = annotate_size, color = "blue") +
  annotate(geom = "text", x = "2020-07", y  = 15000,
              label = "Women", size = annotate_size, color = "gray30" ) +
  annotate(geom = "text", x = "2020-07", y = 70000,
              label = "Men", size = annotate_size, color = "brown" ) 

yoy_unemp_benefit_number <- yoy_unemp_benefit_number + 
  geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

yoy_unemp_benefit_number 

ggplotly(yoy_unemp_benefit_number)

8.3 Benefit amounts/失業給付支給金額

  • Not used in the paper
unemp_benefit_yen <- ggplot(data = graphs_data) +  
  geom_line(aes(x = year_month, y = unemp_benefit_yen_total, group = 1),
           stat = "identity", position = "identity", color = "blue") + 
  geom_line(aes(x = year_month, y = unemp_benefit_yen_female, group = 1), 
             stat = "identity", position = "identity", color = "gray30") +
   geom_line(aes(x = year_month, y = unemp_benefit_yen_male, group = 1), 
             stat = "identity",position = "identity", color = "brown") +
  geom_vline(xintercept =  "2020-01", colour = "gray") +
  theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 0)) +
  theme(plot.title = element_text(size = 10)) +
   labs(title = "The amount of unempolyment benefits") +
  annotate(geom = "text", x = "2019-02", y = 50000000000,
             label = "Total", size = annotate_size, color = "blue") +
  annotate(geom = "text", x = "2019-02", y  = 30000000000,
             label = "Women", size = annotate_size, color = "gray30" ) +
  annotate(geom = "text", x = "2019-02", y = 15000000000,
             label = "Men", size = annotate_size, color = "brown" ) 
  
unemp_benefit_yen <- unemp_benefit_yen + geom_rect(aes(xmin="2020-04",xmax="2020-06", ymin = -Inf, ymax = Inf), # 2021Aug17  網掛け追加
                   fill = "gray70", alpha = 0.01)

unemp_benefit_yen

ggplotly(unemp_benefit_yen)

9 Merge graphs/グラフ統合

# 2020Jan29
# Use patchwork

g <- (emp_labor + unemp_jobapps) / (suicide + yoy_suicide) / 
 (unemp_benefit_number + safety_net)/ (public_assistance + YOY_public_assistance)

g

# 2020Jan29
# Use patchwork
g_updated_UB_level_ver <- (emp_labor + unemp_jobapps) / (suicide + yoy_suicide) / 
 (unemp_benefit_number + safety_net)/ (public_assistance_yoy + YOY_public_assistance)

g_updated_UB_level_ver

# 2021Nov4 
# Use patchwork
g_updated <- (emp_labor + unemp_jobapps) / (suicide + yoy_suicide) / 
 (yoy_unemp_benefit_number + safety_net)/ (public_assistance_yoy + YOY_public_assistance)

g_updated

# 2021Aug13 

# Font for windows and mac
if(stringr::str_detect(path, pattern="D:")){ 
  
ggplot2::ggsave(file = "output/graphs_time_series.pdf",  plot = g, dpi = 100, width = 10, height = 12)

 } else{
  # for mac (ggsaveで出力できず)
  # pngで出力
quartz(file = "output/graphs_time_series.pdf", family = "sans", type = "pdf",
       width = 12, height = 14)
print(g)
dev.off()

 }
## quartz_off_screen 
##                 2
#if(stringr::str_detect(path, pattern="/Users")){
  # for mac (ggsaveで出力できず)
# pngで出力
#quartz(file = "graphs_time_series.pdf", family = "sans", type = "pdf",
#       width = 12, height = 14)
#print(g)
#dev.off()
#}else{
  # for windows
# pngで出力
#ggplot2::ggsave(file = "graphs_time_series.pdf", dpi = 300, width = 10, height = 12, plot = g)

#ggplot2::ggsave(file = "graphs_time_series.pdf",  plot = g, dpi = 100, width = 10, height = 12)
#}
# 2021NOv4 
if(stringr::str_detect(path, pattern="/Users")){
# for mac (ggsaveで出力できず)
# pngで出力
quartz(file = "output/graphs_time_series_updated.pdf", family = "sans", type = "pdf",
       width = 12, height = 14)
print(g_updated)
dev.off()
}else{
  # for windows

ggplot2::ggsave(file = "output/graphs_time_series_updated.pdf",  plot = g_updated, dpi = 100, width = 10, height = 12)
}
## quartz_off_screen 
##                 2
# 2021Aug13 
if(stringr::str_detect(path, pattern="/Users")){
  # for mac (ggsaveで出力できず)
# pngで出力
quartz(file = "output/graphs_time_series_updated_UB_level_ver.pdf", family = "sans", type = "pdf",
       width = 12, height = 14)
print(g_updated_UB_level_ver)
dev.off()
}else{
  # for windows
  
ggplot2::ggsave(file = "output/graphs_time_series_updated_UB_level_ver.pdf",  plot = g_updated_UB_level_ver, dpi = 100, width = 10, height = 12)
}
## quartz_off_screen 
##                 2